Modern security and surveillance systems have come to rely very heavily on the use of video surveillance cameras for the monitoring of remote locations, entry/exit points of buildings or other restricted areas, and high-value assets, etc. The majority of surveillance video cameras that are in use today are analog. Analog video surveillance systems run coaxial cable from closed circuit television (CCTV) cameras to centrally located videotape recorders or hard drives. Increasingly, the resultant video footage is compressed on a digital video recorder (DVR) to save storage space. The use of digital video systems (DVS) is also increasing; in DVS, the analog video is digitized, compressed and packetized in IP, and then streamed to a server.
More recently, IP-networked digital video systems have been implemented. In this type of system the surveillance video is encoded directly on a digital camera, in H.264 or another suitable standard for video compression, and is sent over Ethernet at a lower bit rate. This transition from analog to digital video is bringing about long-awaited benefits to security and surveillance systems, largely because digital compression allows more video data to be transmitted and stored. Of course, a predictable result of capturing larger amounts of video data is that more personnel are required to review the video that is provided from the video surveillance cameras. Advantageously, storing the video can reduce the amount of video data that is to be reviewed, since the motion vectors and detectors that are used in compression can be used to eliminate those frames with no significant activity. However, since motion vectors and detectors offer no information as to what is occurring, someone still must physically screen the captured video to determine suspicious activity.
Another disadvantage of network-based video surveillance and centralized video monitoring solutions is that the network may become overloaded due to the large amount of video data that is involved. This problem is particularly severe when the traffic has to pass over a wide area network, where a service provider typically is charging for the transit of data. In such systems, video data are transmitted constantly to a central location or server for processing and storage. When the video data are to be viewed, additional bandwidth is needed to retrieve the stored information. Of course, a significant amount of video that is recorded today does not contain any relevant or actionable data. For instance, a surveillance camera may record video for hours before a person of interest walks into the field of view, or a suspicious car drives into a monitored parking lot late at night. As a result, there has been a push to develop methods that significantly increase the effectiveness of monitoring security and surveillance video.
The market is currently seeing a migration toward IP-based hardware edge devices with built-in video analytics, such as IP cameras and encoders, including passive infrared (PIR) based motion detection, analytics on a box, etc. Video analytics electronically recognizes the significant features within a series of frames and allows the system to issue alerts when specific types of events occur, thereby speeding real-time security response. Automatically searching the captured video for specific content also relieves personnel from tedious hours of reviewing the video, and decreases the number of personnel that is required to screen the video. Furthermore, when ‘smart’ cameras and encoders process images at the edge, they record or transmit only important events, for example only when someone enters a predefined area that is under surveillance, such as a perimeter along a fence. Accordingly, deploying an edge device is one method to reduce the strain on the network in terms of system requirements and bandwidth.
Unfortunately, deploying ‘smart’ cameras and encoders or analytics on DVR at the edge carries a significantly higher cost premium compared to deploying a similar number of basic digital or analog cameras. Since the analytics within the cameras is designed into the cameras, there is a tradeoff between flexibility and cost, with higher cost solutions providing more flexibility. In essence, to support changing functionality requires a new camera or a significantly higher cost initial camera or local DVR.
Accordingly, it would be advantageous to provide a method and system that overcomes at least some of the above-mentioned limitations.